Blog

Does Bollinger Band Breakout Actually Work? Trend-Following and Squeeze Variants

Bollinger Bands are usually introduced as a mean-reversion tool, but they can also be used as a breakout signal riding the "band walk" during strong trends. We break down the ±2σ breakout and the squeeze breakout variants, and what to watch for in backtests.

Donchian Channel Breakout: Backtesting the Turtle Traders' Core Strategy

Donchian channel breakout is the backbone of the famous Turtle Traders experiment — buy the 20-day high, exit on the 10-day low. We walk through the classical structure and ask whether it still holds up on modern equities in a backtest.

Ichimoku Kumo Breakout: What Happens When You Mechanize the Five-Line Indicator

Ichimoku Kinko Hyo uses five lines and is famously built for visual, holistic reading — making it hard to backtest. We narrow the scope to the cloud (Kumo) breakout and examine how the rule behaves when coded up mechanically.

Why QuanTest Is Local-First: Keeping Price Data on Your Device

QuanTest runs backtests entirely on your device — price data is never sent to our servers. We explain the design choice, how it differs from cloud-based tools, what it means practically for individual traders, and where we do use the cloud.

Reading MACD Signals: Can the Histogram Front-Run Trend Reversals?

MACD is popular as a "leading" version of a moving average cross, but in backtests it mixes genuine leads with frequent whipsaws. We break down three ways to use it — signal cross, zero-line cross, and histogram reversal — and their appropriate market regimes.

Monte Carlo Simulation: Stripping Luck Out of Your Backtest

A backtest equity curve is just one realization — change the trade order and the drawdown picture changes with it. Monte Carlo simulation evaluates strategy robustness by shuffling trade order or sampling from the return distribution.

Position Sizing 101: Fixed Fractional, ATR-Based, and Kelly

How much you trade often matters more than what you trade. We walk through the three classic position-sizing frameworks — fixed fractional, ATR-based, and Kelly — along with what to look at in your backtest when you switch between them.

Sharpe vs. Sortino: Understanding How "Downside Risk" Changes the Verdict

Sharpe ratio is the default risk-adjusted return metric, but its symmetric treatment of volatility can be unfair. Sortino ratio fixes this by measuring only downside deviation. We explain when each matters.

Why Ignoring Fees and Slippage in Your Backtest Is Dangerous

A backtest with zero fees and zero slippage always looks better than reality. For active strategies, modeling (or not modeling) costs can completely invert the ranking of strategies. We break down a minimum viable cost model.

What Is Walk-Forward Analysis? Escaping the Past-Optimization Trap

Running a single backtest over an entire history invites curve-fitting to the past. Walk-forward analysis (WFA) repeatedly trains on one window and tests on the next, borrowing a cross-validation mindset from machine learning to measure generalization.

Do Golden Cross and Death Cross Actually Work? Testing Moving Average Cross Strategies

Do golden cross and death cross signals really work? We break down the moving average cross strategy's assumptions, suitable market conditions, pitfalls, and how 5/25, 25/75, and 50/200 parameter pairs differ in practice.

RSI Contrarian Strategy Thresholds (30/70, 25/75, 20/80) and Their Pitfalls — A Backtesting Guide

When does RSI 30/70 actually work, and when does it fail? A walkthrough of threshold selection (30/70, 25/75, 20/80), the mean-reversion assumption, the classic "catching a falling knife" pattern, and what to check in your backtests.

5 Metrics to Watch When Comparing Backtest Results — Return, Max Drawdown, Sharpe Ratio, and More

Picking strategies by return alone leads to poor decisions. A walkthrough of the 5 metrics to compare — max drawdown, Sharpe ratio, trade count, win rate, and P&L per trade — and how to read each one.

Why QuanTest Chose CSV Import — A Local-First Design Supporting SBI, Rakuten, and Yahoo! JAPAN

Why manual CSV import? We walk through the local-first design choice — keeping price data off external servers — and QuanTest's support for SBI (HYPER SBI 2), Rakuten (MarketSpeed II), and Yahoo! JAPAN Finance, plus the tradeoffs.

4 Checkpoints for Avoiding Overfitting in Backtests

The more parameters you tune, the better your backtest looks — but that doesn't translate to future performance. A walkthrough of 4 core disciplines for avoiding overfitting, including in-sample/out-of-sample splits and sensitivity analysis.

What Is Survivorship Bias in Backtesting? The Hidden Reason Results Look Too Good

Backtesting against today's stock list makes your results look more optimistic than reality. A walkthrough of how survivorship bias works, how large the impact is by universe and period, and practical mitigations for individual investors.